Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models

Table 1 Analysis of prostate cancer data.

Covariate	Estimate	S.E.	P-value
Intercept	0.9893	2.7552	0.7205
Age	-0.0140	0.0425	0.7430
τ	4.7362	3.6190
ρ	1.9093	0.6603
Score test for the genetic pathway effect H₀: h(z) = 0:
Test	P-value
KM	< 0.0001
GT	0.0661

Parameter estimates and score test of the logistic kernel machine regression model for the genetic pathway effect applied to the prostate cancer data. In the table, KM stands for Kernel machine method using the Gaussian kernel, and GT for global test of Geoman et al. [13] assuming linearity.

ISSN: 1471-2105